Emerging trends in molecular recognition: utility of weak aromatic interactions

Aromatic interactions play a vital role in chemistry and biology. As about 20% are aromatic in nature, so the role of aromatic interactions become prominent in drug receptor interactions. Not only in drug receptor interactions but also in crystal engineering, protein folding, stacking interactions in DNA/RNA the role of the interactions is of utmost importance. With the emergence of supramolecular chemistry dendrimers, tweezers, rotaxanes, catenanes, and several supramolecular aggregates are associated with aromatic interactions. The mechanism of such interactions is still unknown by the replacement of a small substituent from the aromatic molecule may lead or destroy the interactions. In the present review several models are being discussed with arene interactions under selected heads.     

Nature of cation-π interactions and their role in structural stability of immunoglobulin proteins

Cation-π interactions are known to be important contributors to protein stability and ligand-protein interactions. In this study, we have analyzed the influence of cation-π interactions in single chain immunoglobulin proteins. We observed 87 cation-π interactions in a data set of 33 proteins. These interactions are mainly formed by long-range contacts, and there is preference of Arg over Lys in these interactions. Arg-Tyr interactions are predominant among the various pairs analyzed. Despite the scarcity of interactions involving Trp, the average energy for Trp-cation interactions is quite high. This information suggests that the cation-π interactions involving Trp might be of high relevance to the proteins. Secondary structure analysis reveals that cation-π interactions are formed preferably between residues in which at least one is in β-strand. Proteins having β-strand regions have the highest number of cation-π interaction-forming residues.     

蛋白质相互作用的生物信息学研究进展

生命过程的分子基础在于生物分子之间的相互作用,其中蛋白质分子之间的相互作用占有极其重要的地位。研究蛋白质相互作用对于理解生命的真谛、探讨致病微生物的致病机理,以及研究新药提高人们的健康水平具有重要的作用。用生物信息学的方法研究蛋白质的相互作用已经取得了许多重要的成果,但也有很多问题还需解决。本文从蛋白质相互作用的数据库、预测方法、可预测蛋白质相互作用的网上服务、蛋白质相互作用网络等几方面,对蛋白质相互作用的生物信息学研究成果及其存在的问题做了概述。     

高阶相互作用对宿主-寄生群落动态的影响

物种间相互作用是影响生物群落稳定性和多样性的重要因素。基于Lotka-Volterra竞争模型,通过构建多宿主种群的种内和种间高阶相互作用模型,研究宿主种群的间接竞争效应对寄生群落动态的影响机制。为有效地揭示高阶作用对种群动态的影响,通过对比宿主-寄生群落的现象模型以及机制模型,利用机制模型产生的合理数据集对现象模型中高阶项的参数进行拟合,进而探讨了高阶相互作用在群落动态中的作用。结果显示,完整的高阶相互作用模型在描述多宿主-寄生系统的群落动态中表现最优,而直接相互作用模型对群落动态的描述相对较差,即同时考虑种间和种内的高阶相互作用模型更加符合机制模型所描述的群落动态。此外,种内高阶作用和种间高阶作用产生不对称效应,宿主间的种间高阶作用对群落产生的影响较种内高阶作用更为显著。该研究结果在一定意义上丰富了宿主-寄生生物群落的稳定性研究,为理解物种间相互作用的多样性研究提供了依据。     

Geometric cooperativity and anticooperativity of three-body interactions in native proteins

Characterizing multibody interactions of hydrophobic, polar, and ionizable residues in protein is important for understanding the stability of protein structures. We introduce a geometric model for quantifying 3-body interactions in native proteins. With this model, empirical propensity values for many types of 3-body interactions can be reliably estimated from a database of native protein structures, despite the overwhelming presence of pairwise contacts. In addition, we define a nonadditive coefficient that characterizes cooperativity and anticooperativity of residue interactions in native proteins by measuring the deviation of 3-body interactions from 3 independent pairwise interactions. It compares the 3-body propensity value from what would be expected if only pairwise interactions were considered, and highlights the distinction of propensity and cooperativity of 3-body interaction. Based on the geometric model, and what can be inferred from statistical analysis of such a model, we find that hydrophobic interactions and hydrogen-bonding interactions make nonadditive contributions to protein stability, but the nonadditive nature depends on whether such interactions are located in the protein interior or on the protein surface. When located in the interior, many hydrophobic interactions such as those involving alkyl residues are anticooperative. Salt-bridge and regular hydrogen-bonding interactions, such as those involving ionizable residues and polar residues, are cooperative. When located on the protein surface, these salt-bridge and regular hydrogen-bonding interactions are anticooperative, and hydrophobic interactions involving alkyl residues become cooperative. We show with examples that incorporating 3-body interactions improves discrimination of protein native structures against decoy conformations. In addition, analysis of cooperative 3-body interaction may reveal spatial motifs that can suggest specific protein functions.     

Studies on protein folding, unfolding and fluctuations by computer simulation. III. Effect of short-range interactions.

The theoretical model of proteins on the two-dimensional square lattice, introduced previously, is extended to include the specific short-range interactions. Attractive long-range interactions with various specificities and non-specific repulsive long-range interactions in the form of self-avoidance of the polymer chain are also operative in the model. Dynamics of the model protein is studied by a Monte Carlo method. The short-range interactions are found to accelerate the folding and unfolding transitions. Non-specific part of the attractive long-range interactions have a competing effect of decelerating the transitions. When the short-range interactions are weighted beyond a certain extent over the attractive long-range interactions are weighted beyond a certain extent over the attractive long-range interactions, the all-or-none character of the folding and unfolding transitions is destroyed. How the destruction proceeds is quantitatively expressed in terms of the S-H curves. The limiting case of dominance of the specific short-range interactions over the attractive long-range interactions is studied in detail. The lattice polymer in this limit does not behave like a globular protein at all. This observation leads to a reexamination of the currently popular notion of the dominance of the short-range interactions. A new concept of consistency is proposed to replace it. Possible mechanisms of the acceleration of the transitions by the specific short-range interactions are discussed.     

Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertoires in the PDB and yeast

In the postgenomic era, one of the most interesting and important challenges is to understand protein interactions on a large scale. The physical interactions between protein domains are fundamental to the workings of a cell: in multi-domain polypeptide chains, in multi-subunit proteins and in transient complexes between proteins that also exist independently. To study the large-scale patterns and evolution of interactions between protein domains, we view interactions between protein domains in terms of the interactions between structural families of evolutionarily related domains. This allows us to classify 8151 interactions between individual domains in the Protein Data Bank and the yeast Saccharomyces cerevisiae in terms of 664 types of interactions, between protein families. At least 51 interactions do not occur in the Protein Data Bank and can only be derived from the yeast data. The map of interactions between protein families has the form of a scale-free network, meaning that most protein families only interact with one or two other families, while a few families are extremely versatile in their interactions and are connected to many families. We observe that almost half of all known families engage in interactions with domains from their own family. We also see that the repertoires of interactions of domains within and between polypeptide chains overlap mostly for two specific types of protein families: enzymes and same-family interactions. This suggests that different types of protein interaction repertoires exist for structural, functional and regulatory reasons. Copyright 12001 Academic Press.     

Disentangling the web of allosteric communication in a homotetramer: heterotropic activation in phosphofructokinase from Escherichia coli

Phosphofructokinase from Escherichia coli (EcPFK) is a homotetramer with four active sites and four allosteric sites. Understanding the allosteric activation of EcPFK by MgADP has been complicated by the complex web of possible interactions, including active site homotropic interactions, allosteric site homotropic interactions, and heterotropic interactions between active and allosteric sites. The current work has simplified this web of possible interactions to a series of single heterotropic interactions by forming and isolating hybrid tetramers. Each of the four unique heterotropic interactions have independently been isolated and compared to a control that has all four of the unique heterotropic interactions. If the interactions are labeled with the distances between interacting ligands, the 45-A interaction contributes 20% +/- 1%, the 33-A interaction contributes 34% +/- 1%, the 30-A interaction contributes 21% +/- 1%, and the 23-A interaction contributes 25% +/- 1% with respect to the total free energy of MgADP/fructose 6-phosphate (Fru-6-P) activation in the control. The free energies of the isolated interactions sum to 100% +/- 2% of the total. Therefore, the four unique interactions are all contributors to activation, are nonequivalent, and are additive.     

Integrative approach for computationally inferring protein domain interactions

MOTIVATION: The current need for high-throughput protein interaction detection has resulted in interaction data being generated en masse through such experimental methods as yeast-two-hybrids and protein chips. Such data can be erroneous and they often do not provide adequate functional information for the detected interactions. Therefore, it is useful to develop an in silico approach to further validate and annotate the detected protein interactions. RESULTS: Given that protein-protein interactions involve physical interactions between protein domains, domain-domain interaction information can be useful for validating, annotating, and even predicting protein interactions. However, large-scale, experimentally determined domain-domain interaction data do not exist. Here, we describe an integrative approach to computationally derive putative domain interactions from multiple data sources, including protein interactions, protein complexes, and Rosetta Stone sequences. We further prove the usefulness of such an integrative approach by applying the derived domain interactions to predict and validate protein-protein interactions. AVAILABILITY: A database of putative protein domain interactions derived using the method described in this paper is available at http://interdom.lit.org.sg.     

Beta Diversity of Plant-Pollinator Networks and the Spatial Turnover of Pairwise Interactions

Interactions between species form complex networks that vary across space and time. Even without spatial or temporal constraints mutualistic pairwise interactions may vary, or rewire, across space but this variability is not well understood. Here, we quantify the beta diversity of species and interactions and test factors influencing the probability of turnover of pairwise interactions across space. We ask: 1) whether beta diversity of plants, pollinators, and interactions follow a similar trend across space, and 2) which interaction properties and site characteristics are related to the probability of turnover of pairwise interactions. Geographical distance was positively correlated with plant and interaction beta diversity. We find that locally frequent interactions are more consistent across space and that local flower abundance is important for the realization of pairwise interactions. While the identity of pairwise interactions is highly variable across space, some species-pairs form interactions that are locally frequent and spatially consistent. Such interactions represent cornerstones of interacting communities and deserve special attention from ecologists and conservation planners alike.     

Predicting novel RNA-RNA interactions

The purpose of this article is to give a brief, yet concise overview of the current computational methods for predicting novel RNA-RNA interactions, that is interactions whose characteristic features we do not yet know. We start by briefly reviewing experimentally confirmed examples of RNA-RNA interactions before introducing computational methods for predicting RNA-RNA interactions. We will focus primarily on the interactions between different RNA molecules, that is trans RNA-RNA interactions, and will only discuss methods for predicting RNA structure, that is cis-only RNA-RNA interactions, where this helps to gain a better understanding. We conclude by discussing the merits of the different approaches and provide an outlook on probably and desirable future developments in the field.     

The relative importance of positive and negative interactions for pollinator attraction in a plant community

Plant–pollinator interactions provide ideal frameworks for studying interactions in plant communities. Despite the large potential influence of such interactions on plant community structure, biodiversity and evolutionary processes, we know surprisingly little about the relative importance of positive and negative interactions among plant species for pollinator attraction. Therefore, we explored the relationships between conspecific and heterospecific floral densities and the flower visitation rates of nine plant species mainly visited by bumble bees, and six plant species mainly visited by flies, in a temperate grassland, through stepwise multiple regressions. Significant relationships were interpreted as interactions for pollinator attraction. Our results revealed that positive intra- and interspecific interactions for pollinator attraction were far more frequent than negative ones. Seventeen interspecific interactions were revealed of which 14 were significantly positive, whereas three of four significant intraspecific interactions were positive. Seven species experienced only positive interactions and two species experienced only negative interactions. The results presented here indicate that negative interactions are not necessarily the dominant ecological interaction for pollination among plants within a community, and the study represents a straightforward approach to study intra- and interspecific interactions among multiple species within a community. We discuss which mechanisms may drive the positive interactions for pollinator attraction and whether this may result in facilitative effects on reproductive success. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The diversity of physical forces and mechanisms in intermolecular interactions

Intermolecular interactions became an inherent part of the structure-function paradigm. Therefore, the generalized concept of protein stability and interactions should consider the balance of stabilizing forces working in different types of intermolecular interactions. We consider here two 'extremes' of protein interactions, viral protein with high intrinsic disorder and hyperthermostable protein complexes. Intermolecular interactions provide folding upon binding as a part of function in the viral case, while they secure and stabilize specific native interfaces as a prerequisite for function in hyperthermostable complexes. We propose a generalized concept of protein stability and interactions, which includes intermolecular interactions comprising distinct combinations of stabilizing forces depending on the types of interacting partners.     

Behavioural strategies during intermale agonistic interactions in a cockroach

Intermale interactions of the American cockroach, Periplaneta americana, were analysed in order to determine what behavioural strategies individuals employ. Longer interactions have a greater tendency to contain escalated (dangerous) acts. The nature of the initial dyad (act of the initiator and response of the other individual) of an interaction changes with the length of the interaction, although there is considerable overlap between the ways in which interactions of different lengths begin. Interaction lengths are non-randomly distributed, with an excess of long and short interactions and a deficiency of interactions of intermediate length. In short interactions the initiator is the probable winner: in intermediate length interactions the initiator and non-initiator win equally often; and in long interactions the non-initiator is the probable winner. Being the first individual to escalate a fight confers an advantage only in very short interactions.     

Augmented transitive relationships with high impact protein distillation in protein interaction prediction

Predicting new protein-protein interactions is important for discovering novel functions of various biological pathways. Predicting these interactions is a crucial and challenging task. Moreover, discovering new protein-protein interactions through biological experiments is still difficult. Therefore, it is increasingly important to discover new protein interactions. Many studies have predicted protein-protein interactions, using biological features such as Gene Ontology (GO) functional annotations and structural domains of two proteins. In this paper, we propose an augmented transitive relationships predictor (ATRP), a new method of predicting potential protein interactions using transitive relationships and annotations of protein interactions. In addition, a distillation of virtual direct protein-protein interactions is proposed to deal with unbalanced distribution of different types of interactions in the existing protein-protein interaction databases. Our results demonstrate that ATRP can effectively predict protein-protein interactions. ATRP achieves an 81% precision, a 74% recall and a 77% F-measure in average rate in the prediction of direct protein-protein interactions. Using the generated benchmark datasets from KUPS to evaluate of all types of the protein-protein interaction, ATRP achieved a 93% precision, a 49% recall and a 64% F-measure in average rate. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.     

XH/<Emphasis Type="Italic">π</Emphasis> interactions with the <Emphasis Type="Italic">π</Emphasis> system of porphyrin ring in porphyrin-containing proteins

Searching structures of porphyrin-containing proteins from the Protein Data Bank revealed that the π system of every porphyrin ring is involved in XH/π interactions, with most of the porphyrins having several interactions. Both five-membered pyrrole rings and six-membered chelate rings are involved in XH/π interactions; the number of interactions with five-membered rings is larger than the number of interactions with six-membered rings. We found interactions with C–H and N–H groups as hydrogen-atom donors; however, the number of CH/π interactions is much larger than the number of NH/π interactions. The amino acids involved in the interactions show a high conservation score. Our results that every porphyrin is involved in XH/π interactions and that amino acids involved in these interactions are highly conserved demonstrate that XH/π interactions play an important role in porphyrin–protein stability. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Use of a biomimetic chromatographic stationary phase for study of the interactions occurring between inorganic anions and phosphatidylcholine membranes

A liquid chromatographic method for the study of ion-membrane interactions is reported. A phosphatidylcholine biomimetic stationary phase was established by loading dimyristoylphosphatidylcholine (DMPC) onto a reversed-phase octadecylsilica packed column. This column was then used to study the interaction of some inorganic anions with the stationary phase by UV and conductivity detection. Ten inorganic anions were selected as model ions and were analyzed with the proposed chromatographic system. Anion-DMPC interactions of differing magnitudes were observed for all of the model anions. Perchlorate-DMPC interactions were strongest, followed by thiocyanate-DMPC, iodide-DMPC, chlorate-DMPC, nitrate-DMPC, bromide-DMPC, chloride-DMPC, fluoride-DMPC, and then sulfate-DMPC. Cations in the eluent, especially H(+) ions and divalent cations such as Ca(2+), showed strong effects on anion-DMPC interactions. The chromatographic data suggest that DMPC interacts with both the anions and the cations. Anion-DMPC interactions were dependent on the surface potential of the stationary phase: at low surface potentials anion-DMPC interactions were predominantly solvation dependent in nature whereas at more positive surface potentials anion-DMPC interactions were predominantly electrostatic in nature. Cation-DMPC interactions served to raise the surface potential, causing the anion-DMPC interactions to vary from solvation dependent to electrostatic. The chromatographic data were used to provide quantitative estimates of the enthalpies of the anion-DMPC interactions.     

The electrostatic contribution to DNA base-stacking interactions.

Base-stacking and phosphate-phosphate interactions in B-DNA are studied using the finite difference Poisson-Boltzmann equation. Interaction energies and dielectric constants are calculated and compared to the predictions of simple dielectric models. No extant simple dielectric model adequately describes phosphate-phosphate interactions. Electrostatic effects contribute negligibly to the sequence and conformational dependence of base-stacking interactions. Electrostatic base-stacking interactions can be adequately modeled using the Hingerty screening function. The repulsive and dispersive Lennard-Jones interactions dominate the dependence of the stacking interactions on roll, tilt, twist, and propellor. The Lennard-Jones stacking energy in ideal B-DNA is found to be essentially independent of sequence.